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SSRN 2022年

作者： Wei, Wen-Jing Lin, Hai-Lan Yang, Yuan Huang, Peng Li, Xin-Yuan Wang, Qiang Zhou, Yao-Yu Key Laboratory of Hunan Province for Water Environment and Agriculture Product Safety College of Chemistry and Chemical Engineering Central South University Hunan Changsha410083 China State Environmental Protection Key Laboratory of Monitoring for Heavy Metal Pollutants International Joint Laboratory of Hunan Agricultural Typical Pollution Restoration and Water Resources Safety Utilization College of Resources and Environment Hunan Agricultural University Changsha410128 China

Nano-silver (Ag-NPs) has been widely applied due to its antibacterial properties, but its toxic hazard is not resolved. Although most Ag-NPs in the environment come from artificial import, the natural generation of Ag-NPs is also discovered. The current discussion does not conduct a more in-depth study on the particle characteristics and stability of naturally generated Ag-NPs, which might be different in migration, transformation and bioavailability. Thus, CPE and SP-ICP-MS were used in combination to quantitatively analyze the naturally generated Ag-NPs and further explore its particle characteristics and stability. Results showed that a conversion behavior of Ag + to Ag-NPs existed in the environmental soil, and the particle size of Ag-NPs was mainly distributed in 30 ~40 nm. Oxygen, illumination, and humic acid could promote the natural generation of Ag-NPs, but had different effects on the stability of Ag-NPs. Ag-NPs would be generated and stabilized under the combined action of fulvic acid and humus. This could become a meaningful basis to deeply explore the toxicological effects of Ag-NPs and control Ag-NPs pollution from different sources, and provide a way to discuss the role and influence of trace metals in geochemical transformations. © 2022, The Authors. All rights reserved.

关键词： Soils

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Air pollution characteristics and their relationship with emissions and meteorology in the Yangtze River Delta region during 2014–2016

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Journal of environmental Sciences 2019年第9期31卷 8-20页

作者： Tao Ma Fengkui Duan Kebin He Yu Qin Dan Tong Guannan Geng Xuyan Liu Hui Li Shuo Yang Siqi Ye Beiyao Xu Qiang Zhang Yongliang Ma State Key Joint Laboratory of Environment Simulation and Pollution Control School of Environment State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing Key Laboratory of Indoor Air Quality Evaluation and Control Tsinghua University Beijing 100084 China Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System Science Tsinghua University Beijing 100084 China National Satellite Meteorological Center Beijing 100081 China College of Resources and Environmental Sciences China Agricultural University Beijing 100094 China

With rapid economic growth and urbanization, the Yangtze River Delta(YRD) region in China has experienced serious air pollution challenges. In this study, we analyzed the air pollution characteristics and their relationship with emissions and meteorology in the YRD region during 2014–2016. In recent years, the concentrations of all air pollutants, except O3,decreased. Spatially, the PM2.5, PM10, SO2, and CO concentrations were higher in the northern YRD region, and NO2 and O3 were higher in the central YRD region. Based on the number of non-attainment days(i.e., days with air quality index greater than 100), PM2.5 was the largest contributor to air pollution in the YRD region, followed by O3, PM10, and ***, particulate matter pollution has declined gradually, while O3 pollution *** conditions mainly influenced day-to-day variations in pollutant concentrations. PM2.5 concentration was inversely related to wind speed, while O3 concentration was positively correlated with temperature and negatively correlated with relative *** air quality improvement in recent years was mainly attributed to emission *** 2014–2016, PM2.5, PM10, SO2, NOx, CO, NH3, and volatile organic compound(VOC)emissions in the YRD region were reduced by 26.3%, 29.2%, 32.4%, 8.1%, 15.9%, 4.5%, and0.3%, respectively. Regional transport also contributed to the air pollution. During regional haze periods, pollutants from North China and East China aggravated the pollution in the YRD region. Our findings suggest that emission reduction and regional joint prevention and control helped to improve the air quality in the YRD region.

关键词： Air pollution Spatiotemporal variation Meteorological condition Emission inventory Regional transport Yangtze River Delta

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Insight into the critical factors determining the particle number concentrations during summer at a megacity in China

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Journal of environmental Sciences 2019年第1期31卷 169-180页

作者： Baoshuang Liu Xiaohui Bi Jiaying Zhang Jie Yuan Zhimei Xiao Qili Dai Yinchang Feng Yufen Zhang State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Center for Urban Transport Emission Research College of Environmental Science and EngineeringNankai University Tianjin Environmental Monitoring Center

To identify the critical factors impacting the number concentration of particles with the aerodynamic diameters less than 2.5 μm(PNC_(2.5)), the continuous measurement of PNC_(2.5),chemical components in PM_(2.5), gaseous pollutants and meteorological conditions were conducted at an urban site in Tianjin in June 2015. Results indicated that the average PNC_(2.5) was 2839 ± 2430 d N/dlog Dp 1/cm^3 during the campaign. Compared to other meteorological parameters, the relative humidity(RH) had the strongest relationship with PNC_(2.5), with a Pearson's correlation coefficient of 0.53, and RH larger than 30% influenced strongly PNC_(2.5).The important influence of secondary reactions on PNC_(2.5) was inferred due to higher correlation coefficients between PNC_(2.5) and SO_4^(2-), NO_3^-, NH_4^+(r = 0.78–0.89; p < 0.01) and between PNC_(2.5) and ratios that represent the conversion of nitrogen and sulfur oxides to particulate matter(r = 0.42–0.49; p < 0.01). Under specific RH conditions, there were even stronger correlations between PNC_(2.5) and NO_3^-, SO_4^(2-), NH_4^+, while those between PNC_(2.5) and EC, OC were relatively weak, especially when RH exceeded 50%. Principal component analysis(PCA) and Pearson's correlation analysis indicated that secondary sources, vehicle emission and coal combustion might be major contributors to PNC_(2.5). Backward trajectory and potential source contribution function(PSCF) analysis suggested that the transport of air masses originated from these regions around Tianjin(Liaoning, Hebei, Shandong and Jiangsu) influenced critically PNC_(2.5). The north of Jiangsu, the west of Shandong, and the east of Hebei were distinguished as major potential source-areas of PNC_(2.5) by PSCF model.

关键词： Particle number concentration Correlation analysis Emission sources PSCF

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Semi-analytical model of heat transport around a well with wellbore mixing effect under multi-step flow rate

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Journal of Hydrology 2023年第PartA期625卷

作者： Shi, Wenguang Wang, Quanrong Yan, Haitao Fu, Xiaogang Kuo, Yi-Ming Zhou, Renjie School of Environmental Studies China University of Geosciences 388 Lumo Road Wuhan430074 China State Environmental Protection Key Laboratory of Source Apportionment and Control of Aquatic Pollution Ministry of Ecology and Environment Hubei Wuhan430074 China Hubei Key Laboratory of Yangtze River Basin Environmental Aquatic Science School of Environmental Studies China University of Geosciences Hubei Wuhan430074 China CCCC Second Highway Consultants Co. Ltd. Wuhan430056 China Hebei GEO University Shijiazhuang050031 China Department of Forestry and Natural Resources National Chiayi University 300 Syuefu Rd. Chiayi City60004 Taiwan Department of Environmental and Geosciences Sam Houston State University HuntsvilleTX77340 United States

Modeling heat transport around a well is critical for evaluations of aquifer thermal energy storage (ATES). In this study, an innovative heat transport model considering the wellbore mixing effect under multi-step flow rate in an aquifer system is proposed, where thermal conduction, thermal dispersion, and convection occur in the aquifer. Wellbore mixing effect refers to the influence of mixing processes between the injected water and original water in the well on heat transport in aquifer, which was ignored in existing models. A semi-analytical solution derived from Laplace transform method and Green's function method has been validated by the numerical modeling and field experimental studies. Results show that the wellbore mixing effect should not be ignored in analyzing heat transport around a well in the ATES system, and the new solution satisfactorily interprets the field data. The influence of the thermal dispersion on thermal transfer near the injection/extraction well is sensitive and should not be negligible. Morris global sensitivity analysis demonstrates that the output temperature is most sensitive to the variations of the parameters of wellbore water volume and extraction rate than the others. The influence of water volume decreases with time, and the most sensitive parameter becomes extraction rate in the late stage of the extraction phase. The newly developed model can shed some light on the thermal transfer processes in the ATES system and better interpret the experimental data of the single-well push–pull tests. © 2023 Elsevier B.V.

关键词： Aquifers

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Application of multi-angle spaceborne observations in characterizing the long-term particulate organic carbon pollution in China

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Science of the Total environment 2025年 958卷 177883页

作者： Hang, Yun Pu, Qiang Zhu, Qiao Meng, Xia Jin, Zhihao Liang, Fengchao Tian, Hezhong Li, Tiantian Wang, Tijian Cao, Junji Fu, Qingyan Dey, Sagnik Li, Shenshen Huang, Kan Kan, Haidong Shi, Xiaoming Liu, Yang Gangarosa Department of Environmental Health Rollins School of Public Health Emory University AtlantaGA30322 United States Department of Environmental and Occupational Health Sciences School of Public Health University of Texas Health Science Center at Houston HoustonTX77030 United States Department of Behavioral Science and Health Equity College for Public Health and Social Justice Saint Louis University St. LouisMO63104 United States School of Public Health Fudan University Shanghai200032 China School of Public Health and Emergency Management Southern University of Science and Technology Shenzhen518055 China State Key Laboratory of Environmental Simulation and Pollution Control School of Environment Beijing Normal University Beijing100875 China China CDC Key Laboratory of Environment and Population Health National Institute of Environmental Health Chinese Center for Disease Control and Prevention Beijing100021 China School of Atmospheric Sciences Nanjing University Nanjing210023 China Institute of Atmospheric Physics Chinese Academy of Sciences Beijing100101 China State Ecologic Environmental Scientific Observation and Research Station at Dianshan Lake Shanghai Environmental Monitoring Center Shanghai200235 China Centre for Atmospheric Sciences Indian Institute of Technology Delhi Hauz Khas New Delhi110016 India State Key Laboratory of Remote Sensing Science Aerospace Information Research Institute Chinese Academy of Sciences Beijing100101 China Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention Department of Environmental Science and Engineering Fudan University Shanghai200433 China

Ambient PM2.5 pollution poses a major risk to public health in China, contributing to significant mortality and morbidity. While overall PM2.5 concentrations have declined in recent years, the changes in PM2.5 chemical constituents remain inadequately understood due to limited ground monitoring networks. We developed a Super Learner model that integrates MISR satellite data, chemistry transport model simulations, and land use information to predict daily OC concentrations across China from 2003 to 2019 at a 10-km spatial resolution. The model achieved high predictive accuracy with a cross-validation R2 of 0.84 and an RMSE of 4.9 μg/m3. Our findings show elevated OC levels in Northern China, driven by industrial activities with concentrations exceeding 30 μg/m3 during the heating season. In contrast, forest fires were the primary contributors in Yunnan, raising OC concentrations to 20–30 μg/m3 during fire seasons. Over the 17-year period, the national OC trend declined by 1.3 % annually. Regionally, the Beijing-Tianjin-Hebei region and the Fenwei Plain experienced faster reductions at annual rates of 1.5 % and 2.0 %, respectively, while Yunnan exhibited no significant trends. To better understand pollution source contributions, we analyzed the OC/EC ratio, which indicated higher ratios in less populated rural areas, suggesting agricultural and biogenic emissions, while lower ratios in urban clusters pointed to primary sources such as traffic and industrial activities. Notably, since 2013, significant decreases in the OC/EC ratio have been observed in the North China Plain, likely reflecting the impact of stringent air pollution control policies on biomass burning. This study provides valuable exposure estimates for epidemiological research on the long-term health effects of OC in China, offering insights for evaluating air quality policies and guiding future management strategies. © 2024

关键词： Air quality

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A Label-Free Electrochemical Biosensor for Detection of Uranyl Ions in Water Based on Nucleic Acid Dye-Induced Turn-Oﬀ of Photosensitization

SSRN

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SSRN 2024年

作者： Xiang, Mei Chen, Qiulian Zhu, Guonian Chen, Zhaoxia Li, Hailiang Xu, Shuxia College of Earth Sciences Chengdu University of Technology Sichuan Chengdu610059 China College of Ecology and Environment Chengdu University of Technology Sichuan Chengdu610059 China College of Material and Chemistry & Chemical Engineering Chengdu University of Technology Sichuan Chengdu610059 China State Environmental Protection Key Laboratory of Synergetic Control and Joint Remediation for Soil & Water Pollution Chengdu University of Technology Sichuan Chengdu610059 China

A DNAzyme-based photocatalytic electrochemical biosensor was developed for the label-free detection of uranyl ions (UO22+) in water. In this sensing platform, SYBR Green (SG) molecules were embedded in double-stranded DNA (dsDNA), which was cleaved via formed singlet oxygen (1O2) during photosensitization, causing a significantly declined in the impedance signal of [Fe (CN)6]3-/4-. In the presence of UO22+, the substrate strand was cleaved by the target UO22+, releasing the SG molecule from the dsDNA, and its photosensitive reaction was turned off. Therefore, UO22+ can be sensitive detected based on the change of [Fe (CN)6]3-/4- electrochemical signals. Such a sensing strategy allowed the detection of UO22+ in the concentration range of 1 to 1000 nM, with the detection limit of the method (LOD) of 0.13 nm. The low LOD meets the maximum allowable contamination level (130 nM) of UO22+ in drinking water set by the US environmental protection Agency (EPA). The proposed sensor has been successfully applied to the detection of UO22+ in actual water samples, with recoveries ranging from 87% to 103%. The method, which combines photocatalysis with an electrochemical biosensor, significantly improved the sensitivity for UO22+ detection without the need of labeling and additional signal amplification steps. It is also a promising strategy for on-site and real-time monitoring of UO22+ in environmental water samples. © 2024, The Authors. All rights reserved.

关键词： Potable water

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Earthworm diversity and community assemblage: influencing factors at plot-scale in urban areas

Soil and Environmental Health

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Soil and environmental Health 2024年第2期2卷

作者： Xie, Tian Wang, Meie Chen, Weiping Li, Xuzhi Lyu, Yuexi Sarvajayakesavalu, Suriyanarayanan State Key Laboratory of Urban and Regional Ecology Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing 100085 China University of Chinese Academy of Sciences Beijing 100049 China State Environmental Protection Key Laboratory of Soil Environmental Management and Pollution Control Nanjing Institute of Environmental Sciences Ministry of Ecology and Environment Nanjing 210042 China Department of Chemical Engineering and Biotechnology University of Cambridge Philippa Fawcett Drive Cambridge CB3 0AS United Kingdom Vinayaka Missions Kirubananda Variyar Arts and Science College Vinayaka Missions Research Foundation (Deemed to be University) Tamilnadu Salem 636308 India

Soil fauna including earthworms play a crucial role in various ecosystem functions, thereby contributing to human well-being. The relationships between earthworm populations and environmental factors have frequently been established at regional scales, particularly in urban soils. However, the diversity and community assemblage of earthworms, as well as their influencing mechanism at plot scale, have rarely been studied. Based on the earthworm assemblage from 29 sites in 12 residential communities, the average earthworm abundance, biomass, and species richness were 59.0 individuals/m², 21.7 g/m², and 1.59 species, respectively. Based on a generalized linear mixed model, vegetation distribution pattern, vegetative cover type, and surrounding built environment all affected earthworm biomass. However, none of these residential variables significantly affected its community assemblage. Variation partitioning in canonical ordination revealed that edaphic properties, rather than landscapes, played a significant role in explaining the variation in its community assemblage, with an approximate contribution of 23%. The abundance and biomass of earthworms at the plot-scale in this study were consistent with previous studies at regional scales. However, the species richness at plot scale was lower than those at regional scale, suggesting that earthworm biodiversity may not accurately represent that at a larger scale, species-area relationship. The results indicate a shift in the driving factors of earthworm community assemblage from edaphic property variation at the plot scale to edaphic, historical, and biogeographical heterogeneities at the regional scale. Certain species that are sensitive to key edaphic/landscape parameters are potential candidates for monitoring soil ecological health. © 2024

关键词： Community assemblage Earthworm abundance Edaphic property Generalized linear mixed model Landscape Residential communities Soil fauna Soil health Species richness Urbanization

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Optimization of graph wavenet model for dissolved oxygen prediction using self-distillation and whale optimization algorithm

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Journal of Water Process Engineering 2025年 75卷

作者： Ding, Fei Yuan, Haobin Jiang, Mingcen Yang, Zhiyuan Liu, Hongfei Hao, Shilong Chen, Liangyao Hao, Bing Xie, Xin Li, Wenpan Zhang, Yong Key Laboratory of Beijing for Water Quality Science and Water Environment Recovery Engineering College of Architecture and Civil Engineering Beijing University of Technology Beijing 100124 China State Environmental Protection Key Laboratory of Quality Control in Environmental Monitoring China National Environmental Monitoring Centre Beijing 100012 China School of Engineering and Technology China University of Geosciences Beijing Beijing 100083 China Faculty of Information Technology Beijing University of Technology Beijing 100124 China School of Environment Tsinghua University Beijing 100084 China Beijing Electric Power Economic Research Institute Co. Ltd Beijing 100055 China

Accurate water quality prediction models are crucial for water environment protection. To reduce the complexity of the Graph Wavenet (GWN) model and improve the prediction accuracy of dissolved oxygen (DO), a self-distillation (SD) strategy was employed innovatively and integrated with the whale optimization algorithm (WOA) to optimize the GWN. An innovative DO prediction model (WOA-GWN-SD) was proposed in this study. The model accurately captures the spatiotemporal relationships between sampling sites. Using the self-distillation strategy, a deep teacher model and a shallow student model were trained, simplifying the GWN architecture while maintaining accuracy and efficiency. The whale optimization algorithm was employed to optimize hyperparameters, further enhancing the prediction performance. The model was validated using hourly datasets from 20 sampling sites at Dianchi Lake, China, covering four water quality indicators from January 2022 to February 2024, for DO prediction. The results showed that the WOA-GWN-SD model outperformed the other models, with the performance ranking as follows: WOA-GWN-SD > GWN-SD > GWN > five baseline models. Compared to the GWN model (R² = 0.8286), the R² values of WOA-GWN-SD and GWN-SD improved by 3.27 % and 2.85 %, respectively. Additionally, the WOA-GWN-SD model also demonstrated strong prediction performance in DO prediction using hourly datasets from the Trinity River, USA. Ablation experiments indicated a 0.85 % improvement in R² over GWN, further validating the robustness of the model. This study underscores the effectiveness of the WOA-GWN-SD model in enhancing prediction accuracy and simplifying the GWN architecture. This approach provides a solid foundation for regional water environment protection. © 2025 Elsevier Ltd

关键词： Graph Wavenet Self-distillation Water environment protection Water quality prediction Whale optimization algorithm

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Regionalization based on spatial and seasonal variation in ground-level ozone concentrations across China

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Journal of environmental Sciences 2018年第5期30卷 179-190页

作者： Linjun Cheng Shuai Wang Zhengyu Gong Hong Li Qi Yang Yeyao Wang School of Water Resources and Environment China University of Geosciences China National Environmental Monitoring Center State Environmental Protection Key Laboratory of Quality Control in Environmental Monitoring Lancaster Environment Centre Lancaster University

Owing to the vast territory of China and strong regional characteristic of ozone pollution,it＇s desirable for policy makers to have a targeted and prioritized regulation and ozone pollution control strategy in China based on scientific evidences. It＇s important to assess its current pollution status as well as spatial and temporal variation patterns across *** advances of national monitoring networks provide an opportunity to insight the actions of ozone pollution. Here, we present rotated empirical orthogonal function（REOF）analysis that was used on studying the spatiotemporal characteristics of daily ozone concentrations. Based on results of REOF analysis in pollution seasons for 3 years＇ observations, twelve regions with clear patterns were identified in China. The patterns of temporal variation of ozone in each region were separated well and different from each other, reflecting local meteorological, photochemical or pollution features. A rising trend in annual averaged Eight-hour Average Ozone Concentrations（O3-8 hr） from 2014 to 2016 was observed for all regions, except for the Tibetan Plateau. The mean values of annual and 90 percentile concentrations for all 338 cities were 82.6 ± 14.6 and 133.9 ± 25.8 μg/m3,respectively, in 2015. The regionalization results of ozone were found to be influenced greatly by terrain features, indicating significant terrain and landform effects on ozone spatial correlations. Among 12 regions, North China Plain, Huanghuai Plain, Central Yangtze River Plain, Pearl River Delta and Sichuan Basin were realized as priority regions for mitigation strategies, due to their higher ozone concentrations and dense population.

关键词： Ozone Spatiotemporal variability REOF Regionalizstion

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Antibiotic Resistome and its Driving Factors in an Urban River in Northern China

SSRN

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SSRN 2022年

作者： Wu, Yang Qi, Dianqing Yao, Hong Ren, Jiaoyang Hu, Jingrun Lv, Yitao Yang, Shanqing Sun, Weiling College of Environmental Sciences and Engineering Peking University The Key Laboratory of Water and Sediment Sciences Ministry of Education Beijing100871 China State Environmental Protection Key Laboratory of All Material Fluxes in River Ecosystems International Joint Laboratory for Regional Pollution Control Ministry of Education Beijing100871 China Beijing International Scientific and Technological Cooperation Base of Water Pollution Control Techniques for Antibiotics and Resistance Genes Beijing Key Laboratory of Aqueous Typical Pollutants Control and Water Quality Safeguard School of Civil Engineering Beijing Jiaotong University Beijing100044 China

Urban rivers dynamically influenced by anthropogenic activities are considered as a vital reservoir of antibiotic resistance genes (ARGs). Knowledge on resistome profiles in urban rivers allows better understanding of ARG dissemination, but has not been well explored. Here, a total of 198 ARGs and 12 mobile genetic elements (MGEs) were profiled in water and sediments from the Chaobai river, Beijing. The ARGs with abundances of 1.01×10 6 –3.34×10 8 copies/L in water and 2.92×10 6 –4.58×10 9 copies/g in sediments, dominated by beta-lactamase, displayed a significant seasonal variation. Significant linear correlations between the total abundances of ARGs and MGEs were oberved in the two matrices ( p © 2022, The Authors. All rights reserved.

关键词： Antibiotics

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